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Record W2156308554 · doi:10.2113/gscpgbull.63.1.53

Geochemistry and distribution of biogenic gas in China

2015· article· en· W2156308554 on OpenAlexvenueaboutno aff
Sheng Zhang, Yanmin Shuai

Bibliographic record

VenueBulletin of Canadian Petroleum Geology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsChinaBeijingGeologyIconCitationLibrary scienceDistribution (mathematics)GeochemistryMining engineeringGeographyArchaeologyComputer science

Abstract

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Research Article| March 01, 2015 Geochemistry and distribution of biogenic gas in China Shuichang Zhang; Shuichang Zhang Key Laboratory of Petroleum Geochemistry, China National Petroleum Corporation, Beijing 100083, China Search for other works by this author on: GSW Google Scholar Yanhua Shuai Yanhua Shuai Key Laboratory of Petroleum Geochemistry, China National Petroleum Corporation, Beijing 100083, China Search for other works by this author on: GSW Google Scholar Bulletin of Canadian Petroleum Geology (2015) 63 (1): 53–65. https://doi.org/10.2113/gscpgbull.63.1.53 Article history received: 10 Jun 2014 accepted: 08 Oct 2014 first online: 27 Nov 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Shuichang Zhang, Yanhua Shuai; Geochemistry and distribution of biogenic gas in China. Bulletin of Canadian Petroleum Geology 2015;; 63 (1): 53–65. doi: https://doi.org/10.2113/gscpgbull.63.1.53 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyBulletin of Canadian Petroleum Geology Search Advanced Search Abstract Of twenty-nine known biogenic gas fields in China, three with reserves of nearly 100 × 109 m3 are located in Qaidam Basin, western China, and two with reserves of 50 × 109 m3 are located in Yinggehai Basin, southern China. The other fields, concentrated in eastern and south-eastern China, have smaller reserves. The gas geochemical characteristics, including data from more than 300 gas samples, over 200 isotopic analyses and 12 inert gas analyses, reveals the following. Gases are predominated by methane (CH4) (95%), followed by nitrogen (N2; 0–15%) and carbon dioxide (CO2; <3% but commonly <1%). Methane δ13C1 values are very light, usually <−55‰. The ethane δ13C2 values range widely from −60‰ to −20‰ and the δ13CCO2 values are between −39‰ and 5‰. Hydrogen isotope values of CH4 range from −260‰ to −190‰, which indicate that the gases are formed by CO2 reduction. 3He/4He ratios are between n × 10−8 and n × 10−7. 40Ar/36Ar ratios are between 231 and 439 and R/Ra ratios are 0.03. These biogenic gases exhibit geochemical characteristics and occur in geological settings that indicate two major biogenic gas types in China: early, or primary, biogenic gas and secondary biogenic gas that formed through crude oil biodegradation. Primary biogenic gas reserves are large while secondary biogenic gas reserves are smaller but widely distributed. The geological settings of the two types differ significantly. The primary biogenic gases are concentrated in Cenozoic successions characterized by rapid sedimentation, high organic matter content and syndepositional entrapment. Most secondary biogenic gases are associated with biodegraded heavy oil occurrences and these are not confined to any specific sedimentary strata or epoch. Abstract Parmi vingt-neuf champs gazéifères biogéniques connus en Chine, trois d’entre eux situés dans le bassin de Qaidam, en Chine occidentale, ont des réserves de près de 100 × 109 m3 et deux autres champs, dans le bassin de Yinggehai, en Chine méridionale, possèdent des réserves de 50 × 109 m3. Dans l’Est et le Sud-Est de la Chine, les autres champs contiennent de plus modestes réserves. Les caractéristiques géochimiques du gaz, y compris les données de plus de 300 échantillons gazéifères, plus de 200 analyses isotopiques et 12 analyses de gaz inertes révèlent ce qui suit : dans les gaz, le méthane (CH4) (95 %) prédomine, suivi de l’azote (N2; 0 % à 15 %) et du dioxide de carbone (CO2; <3 % mais souvent <1 %). Les valeurs du méthane δ13c1 sont très modestes, en général <−55‰. Les valeurs pour l’éthane δ13C2 varient largement de −60‰ à −20‰ et pour le δ13CCO2 entre −39‰ et 5‰. Les valeurs de l’isotope de l’hydrogène CH4 varient de −260‰ à −190‰, ce qui indique que les gaz se forment par la réduction du CO2. Les ratios3He/4He s’établissent entre n × 10−8 et à n × 10−7. Les ratios40Ar/36Ar sont entre 231 et 439 et les ratios R/Ra s’établissent à 0,03. Ces gaz biogéniques exposent des caractéristiques géochimiques et apparaissent dans des contextes géologiques indiquant deux types importants de gaz biogéniques en Chine : le gaz biogénique précoce ou primaire et le gaz biogénique secondaire formé au cours de la biodégradation du pétrole brut. Les réserves de gaz biogéniques primaires sont considérables, tandis que les réserves de gaz biogéniques secondaires sont plus modestes, mais plus largement réparties. Le contexte géologique des deux types de gaz diffère considérablement. Les gaz biogéniques primaires sont concentrés dans les successions du Cénozoïque qui se caractérisent par une sédimentation rapide, un degré élevé de matières organiques et un piégeage synsédimentaire. La plupart des gaz biogéniques secondaires sont associées à des indices de pétrole lourd en biodégradation et ceux-ci ne sont pas confinés à des strates ou époques sédimentaires spécifiques.Michel Ory You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score0.526

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.007
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.178
Teacher spread0.172 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations4
Published2015
Admission routes2
Has abstractyes

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